low cost portable system for converting mosul electrical

Al-Rafidain Engineering Journal (AREJ) Vol.26, No.2, October 2021, pp.323-339


Low Cost Portable System for Converting Mosul Electrical

Substations to Smart One’s

Aseel Y. Mohammed Rabee M. Hagem

[email protected] [email protected]

Computer Engineering Department, Collage of Engineering, University of Mosul

Received: 22/6/2021 Accepted: 30/7/2021

ABSTRACT Today electricity supplement still has power failures and blackouts due to the lack of automated analysis and the

utility's low visibility over the grid. Small and undetected electrical problems can have far-reaching consequences. These

failures cause not only high-energy losses, but also costly unscheduled outages, severe injury to employees, and even a

fire. Therefore, the monitoring of electrical substations is essential to detect faults and ensure long-term safe operation,

safety, protection, and reliability. Internet of things technology provides the possibility of obtaining station data in real-

time. In this research, two systems were designed, implemented, and tested in high voltage electric stations. The first part

is designed to obtain data on the environmental conditions at the substations, and the important parameters from the

transmission lines at the substations in real-time, which help to prevent power outages by relying on engineers who can

analyze comprehensively the electrical energy. The system also provides the Automatic Under Frequency Load Shedding

ability if the frequency in the stations falls below the normal limit, which contributes to maintain the efficiency and the

quality of electrical energy in the substations, and provides protection for the substations. The second part is designed to

obtain the values of the parameters that determine the electrical transformers' conditions and monitors the status of the

line in terms of switching off and on in real-time at the substations. Thus, these proposed systems are transforming the

traditional substations into smart substations. The performance of the system is introduced based on correlation of data

and percentage error. The best correlation was for the current data and the least percentage error was for the current.

We strongly believed that the proposed system is vesible.

Keywords:

Smart substations, Smart transformer, IoT, ESP32, Smart monitoring system This is an open access article under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

https://rengj.mosuljournals.com

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1. INTRODUCTION

Electricity is a very handy and useful form of

energy. Electrical power systems are huge and

very complex networks. It is one of the most

critical components of national and global

infrastructure, and its failure has significant direct

and indirect consequences for the economy and

national security[1].

The power grid is made up of power plants,

high-voltage transmission lines, low-voltage

distribution lines, and load centers (residential

and commercial buildings). Transmission lines

carry high-voltage power over vast distances,

whilst distribution lines carry lower-voltage

electricity over shorter distances to homes and

businesses. Transmission and distribution lines

are connected by substations. A substation is

responsible for converting voltages up and down

as well as continuously measuring, monitoring,

safeguarding, and managing its component of the

grid. Electricity continues to be exposed to

blackouts due to a lack of automated analysis and

inadequate knowledge of utilities across the grid

[2].

Systematic electrical substation inspection is

crucial to detect faults, because if left unchecked,

Electrical problems that go unnoticed might have

far-reaching implications. These shortcomings not

only result in excessive energy losses, but they

also result in energy losses that are unneeded. It

also has the potential to cause costly unplanned

outages, catastrophic technical injuries, or a fire.

In order to assure secure long-term operation, the

integrity, protection, and general reliability of this

mailto:[email protected]

324 Aseel Y. Mohammed : Low Cost Portable System for Converting ….


sort of industrial installation, dependable, precise,

and regular inspections are required [3].

With the growing complexity of the power

grid, the infrastructure is seen considered weak

against problems that negatively affect the general

performance and the stability of the network,

although the fault indicators technology has

provided a way to identify faults, the technical

staff still has to make a manual effort and inspect

the devices for longer hours to discover and

determine the fault in the power stations, also

automation of substations has become essential to

increase their efficiency and improve the quality

of the energy provided [4].

Transformers are one of the most critical

elements in substations in electrical power

transmission systems. Some parameters of the

transformer operation are Temperature of oil,

Moisture level, Level of floats, Operation of

cooling fans, Electrical load levels, and Gas

sensors. These levels should be measured

manually periodically by the operating personnel

which will be a tedious and inefficient way of

monitoring, therefore the automation of

transformer in the substation is very important to

allow for a change from periodic and manual to

condition-based maintenance. For efficient power

supply from generation units to end users, reliable

and real-time information is essential to realize

the vision of smart grids. The impact of structural

degradation, natural accidents, and equipment

failures, which cause power disturbances and

outages, can be avoided by online grid condition

monitoring. To maintain grid protection,

reliability, performance, and uptime, there is an

increasing need for intelligent and low-cost

monitoring and control using online sensing

technologies. IoT technology provides an easy

way to monitor problems at the power grid

without spending manual efforts and extra time

[5, 6].

The Internet of Things, commonly abbreviated

as the word (IoT) is a term that has recently

evolved; this refers to the new Internet age that

enables communication and understanding

between interconnected devices, as well as

between separate devices and physical objects.

The goal of the IoT is to use networks to create

connections between objects while minimizing

time and location limitations. The idea of the

Internet of Things (IoT) enables objects to

exchange data for communication purposes

through wired or wireless connections. The IoT's

real-time capability is considered a crucial feature

for monitoring and managing power system

applications. Therefore, machine operators can

use the real-time monitoring system to make

informed decisions on technological as well as

electrical matters in substations. IoT enables the

electricity grid to be measurable (able to be

calculated and visualized), controllable (able to be

optimized and manipulated), and automated (able

to adapt and selfheal) by using sensing, embedded

processing, and wireless communication [7, 8].

A variety of monitoring projects, including

various instruments and technologies, are

deployed in electrical stations. These projects, on

the other hand, are frequently old, pricey, and in

need of renovation to ensure a better execution.

The current project entails, two systems were

designed, each design is dedicated to implement a

specific process, and and including hardware and

software, such as controllers, networks, sensors,

applications, and operating systems. The system

block diagram is shown in fig. 1.

The first system is developed using the

ESP32S microcontroller and Cayenne platform.

PZEM-004T sensor to measure all important

parameters at the same time in substations, these

parameters include (current, voltage, apparent

power, power factor, frequency), and compute

active power and reactive power by relying on the

equations of the power triangle. (DHT11) sensor

to measure (temperature and humidity), and a

relay module to control the break the feeder of

line depending on the frequency value.

The second system is designed to obtain the

values of the oil and winding temperature, from

the transformers in real-time. In addition, it

monitors the status (ON) or (OFF) position of any

Fig 1. Block diagram of the the two different

proposed systems

Aseel Y. Mohammed : Low Cost Portable System for Converting …. 325


feeder line in the substations in real-time, using

the ESP32S microcontroller, Cayenne platform.

Optocoupler (PC817), and HW-685 current to

voltage module.

The tests are accomplished in the real

substations to analyze the performance of the

project and evaluate the operation of the Cayenne

platform.

The remainder of this paper is organized as

follows. Section 2 shows the related works;

section 3 describes the analysis of the first system

design. Section 4 explains the software algorithm

of the first system, section 5 describes the

analysis of the second system design. Section 6

explains the software algorithm of the second

system, section 7 describes the tests and displays

the obtained results, section 8 describes the

systems cost, and section 9 displays the

conclusion and future work.

2. RELATED WORKS

Many ways of monitoring the electric grid

have been the subject of several studies and

researches in the domain of computer science,

electronics, control and automation, electrical,

and technology fields have been carried out that

deal with the different methods of monitoring the

electric grid. Trupti Sudhakar Somkuwar et al. [9]

proposed a system for monitoring and controlling

the electric power transmission line using the

(WSN) (Wireless Sensor Network). The system

reports a failure in the transmission lines and

sends data to the monitoring station, and then the

monitoring station sends a short message (SMS)

to the line operator about the location of the line

where the fault occurred. The system consists of a

microcontroller (Atmega16) that can

communicate with (Google map API (Application

Programming Interface)) to locate the fault and

show it on the area map. Then sending a text

message to the line operator through (GSM)

(Global System for Mobile Communications).

Ravikumar V. Jadhav et al. [10] proposed a

system for monitoring the power distribution

transformer metrics and accessing transformer

data in real-time using the Internet of Things. The

system monitors the primary and secondary

voltages on both sides of the transformer, as well

as the primary and secondary currents from the

supply unit, transformer temperature, active and

reactive power. Matlab Simulink is used to

simulate a three-phase circuit, data is stored in the

database, data is captured in every part of the

circuit and analyzed in real-time by representing

the data in the form of (graphs). These drawings

help the operator in identifying information about

the transformers and continuous monitoring of all

measurements. Mrs. Asha John et al. [11]

proposed an automation system for a power

substation using a built-in processor is (Raspberry

pi) to automate a substation (11kv). The system

consists of meters for current, voltage, active

power, reactive power, and power factor. These

readings are taken from the (RS485) port that

connects to the Raspberry pi in series via (USB)

(Universal Serial Bus). Digital and analog

measurements can be controlled via (GPIO)

(General Purpose Input/Output) pin located in

(Raspberry pi), the system is programmed using

(Codesys IEC611313-3) platform. Rohit R. Pawar

et al. [12] designed a system for monitoring

various gauges in power distribution transformers.

The system consists of two parts. The first part is

(Hardware), consisting of a (PIC18F4550)

(Programmable Integrated Circuit) controller and

various sensors to measure (current, temperature,

oil level, vibration, and humidity), these sensors

considered as input devices to (RTU) (Remote

Terminal Unit), all readings display on the LCD

(Liquid Crystal Display) and the webpage. The

second part is (Software), using SQL (Structured

Query Language). Shilong Li et al. [13] proposed

a system for monitor the oil level in the

transducer tank, using the XS128 microcontroller

and oil level sensor. The oil level sensor is

installed in the glass oil tube, and the control unit

is in the control room of the secondary station, a

signal is sent in real-time to the controlling center

when a height or low oil level in the transformer.

Each oil tank in the transformer is equipped with

an oil level sensor whose output is (4-20 mA), the

current signal for each circuit is converted to a

voltage signal which converted to the actual oil

level in the transformer through specific

equations. Hassan Jama et al. [14] proposed a

system for monitoring and protecting the

distribution transformers based on the Internet of

Things. The system divides into two units, a

control unit, and a monitoring unit. A control unit

consists of a microcontroller (ESP8266-E12),

(current, temperature, and humidity (DHT22))

sensor. The microcontroller collects data

continuously and sends it to the monitoring unit

that uses the (Thingspeak) platform for real-time

monitoring, analysis, and control. Md. Sanwar

Hossain et al. [15] designed a monitoring and

control system for electrical substation

equipment. The system provides sufficient

information to determine the current quality and

quantity of oil in the transformers, when any

alarming situation occurs, the operator is provided

with a warning message with the corrective action

Figure 1. Block diagram of the proposed system



to be taken. The system consists of an

(ATmaga328-P) controller that communicates

with the (ESP8266wifi) unit in a series. The

ultrasonic sensor, to determine the oil level in the

transformer, infrared sensor, to sense the quality

of the transformer oil depending on the radiation

emitted from the oil. Rashmi S et al. [16]

proposed a conductor temperature monitoring

system in the transmission lines, using a

temperature sensor (LM35), an (Atmega AVR)

microcontroller. (WSN) (Wireless Sensor

Network) technology is used to transfer

temperature data from one node to another and

through the microcontroller, data is displayed and

stored on the (Thingspeak) platform. David

Kwabena Amesimenu et al. [17] designed a

system for monitoring the status of distribution

transformers. The system monitors the

transformer temperature, oil level, and three-

phase voltage, in the case of an abnormal

condition, the microcontroller sends a short

message (SMS) containing the abnormal values to

the mobile phone and the central database. The

system consists of an (ATMEGA328P) controller,

a (GSM) modem, a power source, a temperature

sensor (LM35), and a current sensor

(ACS755XCB150). Navaneetha Krishna R et al.

[18] designed a system for detecting the fault

location in the transmission line based on the

concept of Ohm's Law to detect the fault

location.The system consists of an (Arduino)

board, a typical transmission line resistance

(500Ω) for (1km), and a resistance (1kΩ) for

(2km). Manual error entered for display,

(Arduino) works to determine the distance of the

fault occurring with the help of developed

software. The information is transmitted to the

control center through the (Wi-Fi) (Wireless

Fidelity) network.

3. ANALISYS OF THE FIRST SYSTEM

DESIGN

The components of the first system, as well as

the proper connections and the actual position of

each device in the assembly, are shown in fig. 2.

A variable voltage supply 220 volts was used to

test the conversion ratio that was used in the code,

which depended on the line voltage in the real

substation, the power supply was used to supply

the voltage to the microcontroller as well as to the

IoT modem. The components utilized in this

project will be discussed below.

3.1 ESP32 Microcontroller Module

The ESP32 is a dual-core board that is

equipped with two Xtensa LX6 processor boards.

It is launched in September 2016 by Espressif

Systems to replace the μC ESP8266. A powerful

embedded Wi-Fi and Bluetooth unit are included

in the ESP32. The memory is immense (RAM

512KB), (16MB flash). Furthermore, 448KB of

ROM, 520KB of SRAM, and two (8KB) of RTC

memory [19]. ESP32 has 36 GPIOs, 14 of which

are Analog to Digital converters (ADC), ISP pins

used to connect the ESP32 to the SD card reader.

The VCC is given for the ESP32 ranges from

2.2V to 3.6V. Micro USB used to upload the

software and supply power to the board, or uses a

(3.7V) battery to supply it with power [20].

3.2 PZEM-004T sensor

PZEM-004T module is accept an input

voltage of 80 to 260 V AC, a maximum current of

100A, and a rate of 45- 65Hz. It has an embedded

processing capability of SD3004 SoC (produced

by SDIC) specified for electrical power

measurement [21]. The sensor (PZEM-004T) is

used for voltage, current, frequency, power, and

power factor measurements. To easily

communicate with the microcontroller, the circuit

of this sensor depends on the communication

protocol (UART) [22]. PZEM-004T

specifications is:

Supplying voltage: 5VDC;

Input voltage: 80 - 260VAC;

Measuring current: 0-100A;

The frequency of operation: 45 - 65Hz;

Range of power: 26000W;

Interface: 5V TTL UART;

Precision of measurement: grade 1.0

[22].

3.3 DHT11 Sensor The DHT11 is a Temperature and Humidity

Sensor. DHT11 can be correlated with

Microcontrollers such as ESP32, ESP8266,

Raspberry Pi, Arduino, and so on. In the

operating temperature range of 0 to 50°C, it is

capable of calculating relative humidity between

20 and 90 percent RH with an accuracy of ±5

percent RH. The temperature is also measured in

the 0-50°C range with a ±2°C precision. With 8-

bit resolution, all values are returned. This

provides high unwavering efficiency and long-

haul reliability [23].



3.4 Relay module This is a 4-channel relay interface board with

LOW Level 5V, and each channel requires a

driver current of 15-20mA. It can be used to

power several high-current devices and

equipment. It is fitted with AC250V 10A or

DC30V 10A high-current relays. It has a standard

interface that can be directly operate by

microcontrollers. This module is optically isolated

for safety criteria from the high voltage side and

prevents the ground loop when interfacing with

the microcontroller [24].

3.5 Variable power supply 220V AC

This power voltage transformer converter is

designed with a built-in copper coil for long time

use. Featuring a clear voltage output meter. It is

manufactured by "FlowerW", it is dimensions

24.13 x 24.13 x 21.08 cm, and weight is 4.99

Kilograms [25]. It is used to supply the voltage to

the PZEM-004T sensor and obtain initial results.

3.6 My Device Cayenne Platform

The Cayenne platform is used in this project.

The cayenne platform is considered very useful in

IoT applications for being an open-source IoT

platform in addition to being supportive of the

MQTT (Message Queue Telemetry Transport)

protocol, which will be described below.

MQTT: The abbreviation for MQTT is

(Message Queuing Telemetry Transport), which

is a communication protocol. It based on the

(TCP/ IP) protocol used to exchange data over the

Internet. Created in 1999 by IBM, characterized

by ease of use, uncomplicated, lightweight, Low

energy consumption, the transmission of

information very quickly, does not require a large

use of memory. It is also characterize by high

reliability, depending on broker in its work

(MQTT Broker) [26, 27].

My Device Cayenne Platform allows

uploading data for IoT projects and creating

monitoring by creating a free account on

mydevices Cayenne as fig. 3.

4. SOFTWARE ALGORITHM OF THE

FIRST SYSTEM

In this section, we will explain all the

details about the application code that is written

and the programming language that is used to

deploy it.

4.1 Arduino IDE

The Arduino Integrated Development

Environment (IDE) is a programming

Fig. 2 Circuit diagram of the implemented first system hardware

Fig. 3 Create a new account in

Cayenne cloud [28]



environment for ESP32 modules that includes a

content manager for writing code, a toolbar with

standard capabilities, and a series of menus. The

Arduino IDE includes libraries that are

exclusively utilized in this environment. The

benefit of having an open platform is that it does

not require the acquisition of a license, avoiding a

considerable expense. The platform allows you to

create any project that involves several inputs and

outputs. Concerning the IDE programming, C++

was used to recognized and transport data

between ESP32 microcontroller and sensors. In

addition, the Cayenne platform was used to

connect the ESP32 board to the cloud and view

the collected data there [29, 30].

4.2 Power triangle

The power triangle graphically shows the

relationship between active power, reactive

power, apparent power, and power angle. When

the active component (I cosθ) and the reactive

component (I sinθ) of the current are multiplied

by the voltage V, a power triangle is formed, as

shown in the fig.4 [31].

𝑃 = 𝑉 × 𝐼 × 𝑐𝑜𝑠(𝜃) 𝑊𝑎𝑡𝑡 …… (1)

𝑄 = 𝑉 × 𝐼 × 𝑠𝑖𝑛(𝜃) 𝑉𝐴𝑅 …… (2)

𝑆 = 𝑉 × 𝐼 = √𝑃2 + 𝑄2 𝑉𝐴 ...… (3)

𝑃𝐹 =𝑃

𝑆 =

𝑉×𝐼×𝑐𝑜𝑠(𝜃)

𝑉×𝐼 = 𝑐𝑜𝑠(𝜃) ...… (4)

Where, P= Active power, Q= Reactive power,

S= Apparent power, PF= Power factor, 𝜃 = Phase

angle [31, 32].

The power triangle equations as shown in the

above equations were used to calculate the phase

angle value and to use the latter in calculating the

active power and reactive power. As for the

apparent power, despite the ability of the PZEM-

004T sensor to calculate its value, the relationship

between voltage line and voltage phase shown in

equation (5) was adopted, because using a single

sensor is sufficient to measure a single phase

only, while the substation is fed by 3 phases per

line.

𝑉𝐿 = √3 𝑉𝑃 . . … (5)

𝑆 = 3 𝑉𝑃 × 𝐼𝑃 𝑓𝑜𝑟 𝑡ℎ𝑟𝑒𝑒 𝑝ℎ𝑎𝑠𝑒 . . . . (6)

𝐼𝐿 = 𝐼𝑃 . … . (7)

Where, S= apparent power, VL= V Line,

and VP= V Phase, IL=I Line, IP= I Phase [33].

Below is a description of the suggested

algorithm. Furthermore, as illustrated in the

flowchart of fig.5, the cayenne platform is used to

connect the ESP32 board to the cloud as well as

to view the acquired data in the cloud. The flow

of the chart is interrupted whenever the power or

internet is turned off.

5. ANALISYS OF THE SECOND SYSTEM

DESIGN

The measuring devices used in the station

are (Messko st160) [34] as fig. 6, produced by the

German company MR. It was noted that the

(Messko) meter had a signal converter (TT30) to

convert the sensor signals into analog (4- 20mA).

Therefore, sensors that support this feature have

been chosen, and they convert the current

readings into values of oil temperature and

windings, which will be explained in the

following paragraphs.

Fig. 4 Power Triangle [31]

Fig. 6 Messko measuring device [34]



Figure 7 depicts the components of the

second system, as well as the proper connections

and placement of each device in the assembly.

The basic parts of the hardware system consist of

microcontroller ESP32S, explained in details in

section 3, HW-685 current to voltage module, and

optocoupler (PC817), that will be explained

below.

5.1 HW-685 current to voltage module

The HW-685 4-20mA Current Sensing

Module is an input device that provides a usable

output in response to the input measured, this

module can measure currents from 4-20mA.

Board size (42mm × 25mm ×10mm), and weight

(11g). The HW-685 sensor converts the current

measured into voltage. There are two

potentiometers on the module for calibrating the

zero and maximum voltages. With the 4 to 20mA

range, the current is normally (4mA) when the

measured or process variable is at zero and

(20mA) when the measured or process variable is

at full scale [35].

Fig. 5 Flow Chart of the First System



The 4–20 mA current-loop is analog

signaling, it has been a popular method of sending

instrumentation signals. Typically, the measured

physical variable has a minimum value of 4 mA

and a maximum value of 20 mA. A nonzero

minimum current value aids in the detection of

possible transmission issues such as broken wires.

This sensor usually gets its operating power from

the loop (24 V) and doesn't need any additional

power. It has a precision 250-ohm resistor across

the input terminals to convert the 4–20 mA

variance into a 1-to-5 V swing [48]. Fig.8 shows a

4–20 mA current-loop [35, 36].

Equation (8) is used to measure the output

voltage value that corresponds to the input current

value.

𝑃𝑣 =𝑃𝑣ℎ𝑖𝑔ℎ− 𝑃𝑣𝑙𝑜𝑤

𝐼ℎ𝑖𝑔ℎ−𝐼𝑙𝑜𝑤× (𝐼 − 𝐼𝑙𝑜𝑤) + 𝑃𝑣𝑙𝑜𝑤 … (8)

Where, 𝑃𝑣 is a measured physical value,

𝑃𝑣𝑙𝑜𝑤 represents the minimum value of

measurement range, 𝑃𝑣ℎ𝑖𝑔ℎ the maximum value

for measurement range, 𝐼𝑙𝑜𝑤 the minimum value

for current, 𝐼ℎ𝑖𝑔ℎ the maximum value for current,

and 𝐼 the current corresponding to the measured

value [37].

5.2 Linear DC power supply PS-305D

A 30V/5A power supply, it is Brand, Zhaoxin is

reliable. Most medium voltage applications,

MCUs, and motors that require a voltage of 0-

30V can use it, while 0-5A offers ample current

for medium power applications. The big red

display shows precisely what voltage and current

you have set [38]. It is used in this work to supply

the voltage to the HW-685 to calibrate the values

of the input current.

5.3 Calibration of HW-685 Sensor

After connecting the electrical circuit of

the system, Fig. 7, the HW-685 sensor is

calibrated to set the upper and lower limits of the

Fig. 7 Circuit diagram of the implemented second system hardware

Fig.8 4–20 mA current-loop [36]

[51]



input current values and obtain the analog values

for the corresponding voltages from the serial

monitor of the Arduino IDE. The analog voltage,

(3160V) corresponding to (20mA), and (600V)

corresponding to (4mA). The range of the

measuring device is (0 to 150) for a winding

temperature, and (-20 to 140) for an oil

temperature. The span for each scale is calculated

and compensated the resulting values in equation

(8), that discussed above and using this equation

to write the software code to obtain the real

values of the oil temperature and windings from

the measuring devices on the Cayenne platform

in real-time.

𝑃𝑣 =𝑃𝑣ℎ𝑖𝑔ℎ − 𝑃𝑣𝑙𝑜𝑤

𝐼ℎ𝑖𝑔ℎ − 𝐼𝑙𝑜𝑤

× (𝐼 − 𝐼𝑙𝑜𝑤) + 𝑃𝑣𝑙𝑜𝑤

𝑜𝑖𝑙 𝑡𝑒𝑚𝑝. = 140−(−20)

3160−600 × (𝐼 − 600) + (−20) ... (9)

𝑤𝑖𝑛𝑑𝑖𝑛𝑔 𝑡𝑒𝑚𝑝. = 150−0

3160−600 × (𝐼 − 600) + (0) .. (10)

5.4 Optocoupler (PC817)

PC817 is a four-pin optocoupler that

consists of an IRED (Infrared Ray Emitting

Diode) and a phototransistor. The main feature of

PC817 is it connects to the section of the circuit

optically not electrically. The basic operating

concept of PC817 is to pass electrical signals

through light, allowing the circuit to read the

electrical signal and use it as an output. When

there is a power supply on the input side, IRED

emits IR (Infrared Ray) waves and activates the

phototransistor [39].

6. SOFTWARE ALGORITHM OF THE

SECOND SYSTEM

In this section, we will explain all the details

about the application code that was written.

Arduino IDE application, that described in section

4, was used to program the system in C ++

language.

The proposed algorithm is described in the

flowchart of fig. 9. The flow of the chart is ended

at any time that the power or the internet is shut

off.

7. TESTS AND RESULTS

Various tests have been applied in high

voltage substations to assess the efficiency of the

system. Based on IoT technology, all the

important parameters have been remotely

measured and alarms applied in real-time at the

transmission substation. An automatic feeder out

of work has been applied in the proposed system.

In this section, the results of these tests

obtained for the power system are recorded to

illustrate the proposed system efficiency.

7.1 In field test and results for the first system

The proposed monitoring system is

installed and tested in a real power substation

(West Mosul station 132KV), as shown in fig. 10.

Fig. 9 Flow Chart of the second system



In this test, the PZEM-004T sensor is

supplied with an AC input voltage and current

from the output of the secondary transformer for

the (Badush line) at the West Mosul station, and

the sensor is directly connecting to the ESP32S

controller. The results (voltage, current,

frequency, active power, reactive power, apparent

power, and power factor), as well as results of

temperature and humidity from the DHT11

sensor, will be stored on the cloud, and displayed

using the Cayenne platform.

On Jan 18, 2021, data are obtained via the

Cayenne platform after connecting the system to

the station and switching it on, it was checked that

the readings were roughly equal to the real values

in the station's gauges, as shown below; fig. 11

shows the reading of the station's gauges. Fig. 12

shows the results on the Cayenne platform. The

difference between the results obtained on the

Cayenne platform and the readings in the station's

gauges for the values of the voltage, current,

apparent power, and frequency was (0.21), (0.53),

(0.21), and (0.22) sequentially. The error rate is

caused by electromagnetic waves and other noise

sources in the substations.

The system is kept connected to the

station for a week and all readings were obtained

in real time through the Cayenne platform on the

website and mobile application.

The values of the active power and reactive

power can be verified by relying on the equations

of the power triangle, where the apparent power (S)

is equal to the square root of the sum of the square

of the value of the active power (P) and the reactive

power (Q).

Fig.10 Installation at the Substation

Fig.11 Reading of parameters at the station gauges

(a) Voltage (b) Current

(c) Apparent power (d) Frequency



Data are collected for one week in the

Cayenne cloud and displayed on the Cayenne

platform as shown in fig.13, 14, and 15 graphs of

weekly readings of apparent power, voltage, and

frequency. The increase and decrease in the values

are noticed depends on the general performance of

the sub-station. As for the points where there is no

reading in the graphs and shown in a straight line,

this is due to a general interruption in the electrical

network in the city of Mosul.

The graphs in fig. 16 and 17 show the reading of

two channels on the mobile device through the

Cayenne app., this reading for the voltage, and current

for a one hour, from (8:30 pm) to (9:30 pm).

The correlation factor is calculated between

the real values at the substation and the values

read by the Cayenne platform for all parameters. It

it concluded that the correlation factor for voltage

is 0.9902, for current 1, for active energy 0.9996,

and for reactive power 0.9995, as shown in fig. 18,

19, 20, and 21.

Fig. 12 Reading of parameters on the Cayenne

platform

Fig. 13 Graph of apparent power values on Cayenne

website

Fig. 14 Graph of voltage values on Cayenne website

Fig. 15 Graph of frequency values on Cayenne website

Fig. 16 Graph of voltage values on

mobile app.

Fig. 17 Graph of current values on

mobile app.



The percentage error is calculated between the

real values in the substation and the values on the

Cayenne platform for one week for the values of

the voltage, current, active power, and reactive

power as shown in fig. 22. The average percentage

error is calculated as fig. 23, for the values of

voltages (0.32%), current (0.11%), active power

(0.6%), reactive power (0.8%), which indicates the

efficiency and accuracy of the proposed system for

monitoring real-time readings from the substation.

7.2 In-field test and results for the second

system

The proposed monitoring system has been

installed and tested in a real power substation

(Yaremja secondary station 132 kV), as shown in fig.

24.

0.00%0.20%0.40%0.60%0.80%1.00%1.20%1.40%1.60%1.80%2.00%

Voltage Current Active power Reactive power

0.32%

0.11%

0.60%

0.80%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

Voltage Current Active power Reactive power

Fig.18 Correlation factor for the voltage

Fig. 19 Correlation factor for the current

Fig. 20 Correlation factor for the active power

Fig. 21 Correlation factor for the reactive power

Fig. 22 Percentage error for one week

Fig. 23 Average percentage error



In this test, the HW-685 sensor is supplied

with an analog current signal from the signal

converter (TT30) of the measuring devices for the

oil and winding temperature (Messko st160). The

results will be stored on the cloud, and displayed

using the Cayenne platform.

On Apr 13, 2021, data are obtained via the

Cayenne platform after connecting the system to

the station and switching it on, it was checked that

the readings were roughly equal to the real values

in the station's gauges, as shown below; fig. 25

shows the reading of the transformer panel, and the

results on the Cayenne platform.

On March 29, 2021, the electrical line state

monitored via the Cayenne platform after

connecting the proposed system to the auxiliary

switches inside the panel of the electrical line at

West Mosul station 132KV. An out-of-work line

chosen, to test the proposed system, the line is

manually turned off and on, and its condition is

monitored on the Cayenne dashboard. Fig. 26

shown the installation at the substation. Fig. 27

shown the status of line at substation.

8. SYSTEMS COST

The system cost is according to the prices of the

electronic components, written in the table 4.1.

Sub-System 1 Sub-System 2

Component Num Price Component Num Price

ESP32S 1 10 $ ESP32S 1 10 $

PZEM-004T 1 20 $ HW-685 (2) 2 16$

DHT11 1 3$ PC817 (2) 2 14$

Relay 4 channel

1 9$

Total 42$ Total 40$

Fig. 24 Installation at the Yaremja station

Fig. 25 Reading of the transformer panel and

Cayenne dashboard

Table.1 The proposed system cost

Fig. 26 Installation at the West Mosul station

Fig. 27 State of line (a) on state (b) off state



9. CONCLUSION AND FUTURE WORK

9.1 Conclusion

The smart systems are proposed in this paper

for monitoring important parameters in electrical

substations and transformers based on the Internet

of things, to reduce disasters and economic losses in

the important equipment in the stations. The first

proposed system included monitoring of the

important parameters voltage, current, power,

frequency, power factor, active power, reactive

power, temperature, and humidity. Dataare

continuously transmitted and displayed in real-time

on the Cayenne platform through the ESP32S

module. The proposed system is tested at the 132kV

West Mosul station, and readings were obtained in

real-time on the Cayenne website and mobile

application. The correlation factor is calculated

between the real values at the station and the values

on the Cayenne platform. The correlation factor for

voltage is 0.9902%, for current 1%, for active

power is 0.9996%, and for reactive power is

0.9995%. The average percentage error is calculated

for the values of voltages (0.32%), current (0.11%),

active power (0.6%), reactive power (0.8%), which

indicates the efficiency of the designed system that

can be adopted in electric power substations for

transmission and distribution. The second proposed

system included monitoring of the oil and windings

temperature for the electrical transformer for

evaluating the condition and potential for a power

transformer to fail, to reducing unexpected

malfunctions. This system also monitoring the (on)

and (off) state of the electrical line in real-time. The

second proposed system is tested at the Yaremja

secondary station at 132 kV, and readings were

obtained in real-time on the Cayenne website. The

implementation of these systems reduces the

severity of disasters in the stations and is considered

a step for the transition from traditional substations

to smart substations. The amount of systems cost is

(82$), which is very cheap. The system has proven

its feasibility, as the smart substation saves the time

and effort that the engineers and technicians spend

in obtaining the important readings in the stations

and knowing the station's stability, where it can be

recovering. Daily, weekly and monthly data can be

retrieved due to the MQTT cloud supported by the

Cayenne platform.

9.2 Future Work

The following suggestion has been stimulated

during this research.

1) The proposed system can be developed by

linking more than one monitoring system for

multiple substations together so that the

responsible authorities can monitor and control

these systems remotely.

2) The system can be developed to detect the

occurrence of fire in the substations and send

an alert to the responsible authorities to take

the appropriate action.

3) Adding new sensors to the system to improve

its functionality.

4) Adding new hardware to the system, such as a

camera for auto-observation and surveillance,

as well as some facilities that allow for the

implementation of an auto-monitoring alarm

system.

5) The system can be developed by designing an

automatic power factor correction unit to

reduce lost energy in the system and improve

load-carrying capabilities to increase system

stability and efficiency.

ACKNOWLEDGEMENTS

The authors of this paper want to thank the

engineers of the General Company for Northern

Electric Power Transmission, West Mosul

Station, and the Yaremja secondary station to

provide some useful information that reinforces

this paper. In addition, to grant formal

permissions and assistance in visiting stations and

taking pictures that are used in this research.

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لى ذكيةالفرعية الكهربائية في الموصل إنظام محمول منخفض التكلفة لتحويل المحطات

ربيع موفق حاجم محمد أسيل يوسف [email protected] [email protected]

قسم هندسة الحاسوب -كلية الهندسة -جامعة الموصل

الملخص

الكهرباء اليوم يعاني من انقطاع التيار الكهربائي وانقطاع التيار بسبب الافتقار إلى التحليل الآلي وضعف رؤية المرافق على الشبكة تزويدلا يزال ؤدي ، بل تيمكن أن يكون للمشاكل الكهربائية الصغيرة وغير المكتشفة عواقب بعيدة المدى. لا تتسبب هذه الإخفاقات في خسائر كبيرة في الطاقة فحسب

ضرورياً أيضًا إلى انقطاعات مكلفة غير مجدولة، وإصابة خطيرة للموظفين، وحتى نشوب حريق. لذلك، تعد مراقبة المحطات الفرعية الكهربائية أمرًالحصول على بيانات لاكتشاف الأعطال وضمان التشغيل الآمن والسلامة والحماية والموثوقية على المدى الطويل. توفر تقنية إنترنت الأشياء إمكانية ا

للحصول على المحطة في الوقت الفعلي. تم في هذا البحث تصميم وتنفيذ واختبار نظامين في محطات الكهرباء ذات الجهد العالي. تم تصميم الجزء الأول ت الفعلي، والتي تساعد في منع بيانات حول الظروف البيئية في المحطات الفرعية، والمعلمات المهمة من خطوط النقل في المحطات الفرعية في الوق

رة التلقائية على فصل انقطاع التيار الكهربائي من خلال الاعتماد على المهندسين الذين يمكنهم تحليل الطاقة الكهربائية بشكل شامل. يوفر النظام أيضًا القداظ على كفاءة وجودة الطاقة الكهربائية في المحطات الفرعية، الأحمال تحت التردد إذا انخفض التردد في المحطات عن الحد الطبيعي، مما يساهم في الحف

لخط من حيث ويوفر الحماية للمحطات الفرعية. تم تصميم الجزء الثاني للحصول على قيم المعلمات التي تحدد ظروف المحولات الكهربائية وتراقب حالة االي، تعمل هذه الأنظمة المقترحة على تحويل المحطات الفرعية التقليدية إلى محطات إيقاف التشغيل وتشغيله في الوقت الفعلي في المحطات الفرعية. وبالت

انت للتيار. لقد اعتقدنا فرعية ذكية. يتم تقديم أداء النظام بناءً على ارتباط البيانات ونسبة الخطأ. كان الارتباط الأفضل للبيانات الحالية وأقل نسبة خطأ ك تطبيق.بشدة أن النظام المقترح قابل لل

، نظام المراقبة الذكي32إي أس بي ، المحطات الفرعية الذكية، المحولات الذكية، إنترنت الأشياء الكلمات الداله:

.

mailto:[email protected]

low cost portable system for converting mosul electrical

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